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Mid-level generalist data role in Bangalore with popular title and 4-6 years increases competitive density.
Core data-platform skills are transferable, but Hudi/lakehouse specialization increases domain-specific bias.
Explicit 4–6 years plus mandatory Hudi, Airflow, Presto and data-platform experience enforces strict filters.
Design, build, and operate scalable batch and near-real-time data pipelines across product, business, growth, and machine learning use cases.
Manage and improve lakehouse architecture using Apache Hudi and large-scale query platforms like Presto/Trino, including orchestration with Apache Airflow.
Ensure data platform reliability, performance optimization, data quality, and mentor junior engineers while partnering with cross-functional teams to meet data needs.
4-6 years of experience in data engineering, preferably at scale.
Hands-on experience with Apache Airflow or similar orchestration systems; strong knowledge of Presto/Trino and Apache Hudi concepts including copy-on-write vs merge-on-read, upserts, incremental reads, compaction, clustering, schema evolution, and partitioning.
Proficient in SQL and at least one programming language such as Python, Java, or Scala.
Location requirement: Work from Office - Domlur, Bangalore (5 days/week).
Experienced in building reliable ETL/ELT pipelines within complex distributed data processing and storage systems.
Operates with a strong production ownership and debugging mindset with ability to reason trade-offs between freshness, cost, reliability, latency, and complexity.
Skilled at influencing architecture decisions and mentoring others in data modeling, pipeline ownership, data quality, and platform scalability within fast growing data environments.